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The Relationship Between Materialism and Personal Well-Being: A Meta-Analysis

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This meta-analysis investigates the relationship between individuals' materialistic orientation and their personal well-being. Theoretical approaches in psychology agree that prioritizing money and associated aims is negatively associated with individuals' well-being but differ in their implications for whether this is invariably the case. To address these and other questions, we examined 753 effect sizes from 259 independent samples. Materialism was associated with significantly lower well-being for the most widely used, multifaceted measures (materialist values and beliefs, r = -.19, ρ = -.24; relative importance of materialist goals, r = -.16, ρ = -.21), more than for measures assessing emphasis on money alone (rs = -.08 to -.11, ρs = -.09 to -.14). The relationship also depended on type of well-being outcome, with largest effects for risky health and consumer behaviors and for negative self-appraisals (rs = -.28 to -.44, ρs = -.32 to -.53) and weakest effects for life satisfaction and negative affect (rs = -.13 to -.15, ρs = -.17 to -.18). Moderator analyses revealed that the strength of the effect depended on certain demographic factors (gender and age), on value context (study/work environments that support materialistic values and cultures that emphasize affective autonomy), and on cultural economic indicators (economic growth and wealth differentials). Mediation analyses suggested that the negative link may be explained by poor psychological need satisfaction. We discuss implications for the measurement of materialist values and the need for theoretical and empirical advances to explore underlying processes, which likely will require more experimental, longitudinal, and developmental research. (PsycINFO Database Record (c) 2014 APA, all rights reserved).
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PERSONALITY PROCESSES AND INDIVIDUAL DIFFERENCES
The Relationship Between Materialism and Personal Well-Being:
A Meta-Analysis
Helga Dittmar, Rod Bond, and Megan Hurst
University of Sussex Tim Kasser
Knox College
This meta-analysis investigates the relationship between individuals’ materialistic orientation and their
personal well-being. Theoretical approaches in psychology agree that prioritizing money and associated
aims is negatively associated with individuals’ well-being but differ in their implications for whether this
is invariably the case. To address these and other questions, we examined 753 effect sizes from 259
independent samples. Materialism was associated with significantly lower well-being for the most widely
used, multifaceted measures (materialist values and beliefs, r⫽⫺.19, ␳⫽⫺.24; relative importance of
materialist goals, r⫽⫺.16, ␳⫽⫺.21), more than for measures assessing emphasis on money alone
(rs⫽⫺.08 to .11, s⫽⫺.09 to .14). The relationship also depended on type of well-being outcome,
with largest effects for risky health and consumer behaviors and for negative self-appraisals (rs⫽⫺.28
to .44, s⫽⫺.32 to .53) and weakest effects for life satisfaction and negative affect (rs⫽⫺.13
to .15, s⫽⫺.17 to .18). Moderator analyses revealed that the strength of the effect depended on
certain demographic factors (gender and age), on value context (study/work environments that support
materialistic values and cultures that emphasize affective autonomy), and on cultural economic indicators
(economic growth and wealth differentials). Mediation analyses suggested that the negative link may be
explained by poor psychological need satisfaction. We discuss implications for the measurement of
materialist values and the need for theoretical and empirical advances to explore underlying processes,
which likely will require more experimental, longitudinal, and developmental research.
Keywords: materialism, meta-analysis, personal well-being, values, consumer behaviors
“Oh what a void there is in things.” —Persius
Every day, thousands of advertisements tell us that people are
happy, worthwhile, and successful to the extent that they have money,
possessions, and the right image (Dittmar, 2008;Kasser & Kanner,
2004). Yet numerous philosophic and religious perspectives across
both time and culture have suggested that focusing one’s life around
the acquisition of money, possessions, and status saps one’s spirit and
undermines one’s quality of life (see Belk, 1983;Elgin, 1993, for
reviews). Psychoanalytic (Freud, 1908/1959;Horney, 1937) and hu-
manistic/existential (Fromm, 1976;Maslow, 1954;Rogers, 1961)
theorists have tended to agree with this critique of materialism, but it
was not until the mid-1980s and early 1990s that consumer research-
ers (Belk, 1984;Richins & Dawson, 1992) and psychologists (Kasser
& Ryan, 1993) began to explore empirically whether well-being is
negatively associated with a strong focus on materialistic aims. These
early studies found that U.S. respondents report less happiness and life
satisfaction, lower levels of vitality and self-actualization, and more
depression, anxiety, and general psychopathology to the extent that
they believe that the acquisition of money and possessions is impor-
tant and key to happiness and success in life.
Since these early studies, dozens more have replicated and ex-
tended the finding that materialism is negatively associated with
personal well-being. Such results have been documented with a va-
riety of measures of materialism, ranging from Likert-type surveys
(Richins, 2004a) to measures of relative goal importance (Kasser &
Ryan, 1996) to projective measures (Chaplin & John, 2007) to reac-
tion times (Schmuck, 2001;Solberg, Diener, & Robinson, 2004). In
addition to the well-being outcomes cited above, a variety of other
constructs have been associated with materialism, including self-
esteem (Ryan et al., 1999), dysfunctional consumer behaviors (Ditt-
mar, 2005a,2005b), physical health problems (Niemiec, Ryan, &
Deci, 2009), positive and negative affect (Christopher & Schlenker,
2004), and interviewer diagnoses of psychopathology (P. Cohen &
Cohen, 1996). Findings have also been replicated in varying popula-
tions, including children as young as 10 years (Kasser, 2005) and
adults into their 80s (Sheldon & Kasser, 2001), and individuals living
in North America (Richins & Dawson, 1992), Western Europe (Dit-
tmar, 2005b), former Soviet bloc nations (Ryan et al. 1999), the
Middle East (Speck & Roy, 2008), and Asia (Wong, Rindfleisch, &
Burroughs, 2003). Studies conducted across time show that increases
Helga Dittmar, Rod Bond, and Megan Hurst, School of Psychology, Uni-
versity of Sussex; Tim Kasser, Department of Psychology, Knox College.
Correspondence concerning this article should be addressed to Helga
Dittmar, School of Psychology, University of Sussex, Pevensey 1 2B5,
Brighton, England, United Kingdom BN1 9QH. E-mail: h.e.dittmar@
sussex.ac.uk
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Journal of Personality and Social Psychology, 2014, Vol. 107, No. 5, 879–924
© 2014 American Psychological Association 0022-3514/14/$12.00 http://dx.doi.org/10.1037/a0037409
879
in psychopathology and decreases in well-being are associated with
stronger endorsement of materialism by U.S. adolescents (Twenge et
al., 2010) and Norwegian citizens (Hellevik, 2003).
To our knowledge, there has been no recent, systematic, empirical
review of this growing literature. The only meta-analysis we are
aware of, examining life satisfaction and materialism, was conducted
more than 2 decades ago using only seven samples (Wright & Larsen,
1993), and the most comprehensive review of the literature (Kasser,
2002) was not quantitative and is more than a decade old at this point.
Given the large number of studies (some unpublished) that have been
conducted since these earlier reviews and the variety of effect sizes
reported (with raw correlations between materialism and well-being
in single studies ranging from positive, such as .38, Sirgy et al., 1998,
to strongly negative, such as .67, Dittmar & Kapur, 2011;Kasser &
Ryan, 1996), a meta-analysis is timely, topical, and useful for pro-
viding information that allows researchers to estimate empirically the
strength, direction, and consistency of the reported negative relation-
ship between materialism and well-being. A second reason for con-
ducting a meta-analysis now is that materialism appears to be on the
rise among young people (Twenge et al., 2010) at the same time that
personal well-being in economically developed countries is be-
coming an important policy concern (e.g., see the website of the
All-Party Parliamentary Group on Wellbeing Economics, http://
parliamentarywellbeinggroup.org.uk). Thus, a meta-analysis may
help clarify the potential worth of developing interventions, edu-
cational practices, and policies designed to diminish people’s focus
on the acquisition of money and possessions. A final reason for
conducting a meta-analysis is that several questions remain open in
the materialism literature for which meta-analytic techniques are
particularly well placed to provide answers. We now turn to these
methodological and theoretical questions.
Does the Negative Relationship Depend on the Types
of Materialism and Well-Being Measures Used?
Materialism Measures
In line with past work (Dittmar, 2008;Kasser & Kanner, 2004;
Richins, 2004b;Sirgy, 1998), we define materialism for the purposes
of this meta-analysis as individual differences in people’s long-term
endorsement of values, goals, and associated beliefs that center on the
importance of acquiring money and possessions that convey status.
Thus, the current meta-analysis does not include assessments regard-
ing (a) philosophical materialism (i.e., the belief that physical laws
concerning matter can answer most questions), (b) beliefs about the
goals that a society (as opposed to an individual person) should pursue
(as captured, e.g., by Inglehart’s, 1981,1997, materialist and postma-
terialist values), (c) attitudes toward budgeting money or money as
good or bad in general (e.g., Tang, Kim, & Tang, 2002), (d) measures
of purchases made with the intention of acquiring material posses-
sions (as opposed to obtaining experiences; Carter & Gilovich, 2012;
Van Boven & Gilovich, 2003), or (e) measures of power values
(which are primarily concerned with having dominance and status
over other people; Schwartz, 1992; see Kasser & Ahuvia, 2002, for
discussion of this latter distinction). The measures that fit our defini-
tion and are included in the meta-analysis vary in some respects but,
generally speaking, follow one of two broad methodological ap-
proaches (see Table 1). The first approach uses Likert-type scales to
assess agreement with statements representing materialist values, be-
liefs, and behaviors. Some scales measure solely the significance an
individual attaches to being wealthy (Georgellis, Tsitsianis, & Yin,
2009), whereas others assess beliefs associated with money (Tang,
Tang, & Luna-Arocas, 2005) or personality traits linked to material
possessions (Belk, 1984). Researchers have also developed scales to
measure different facets of materialism, such as the Material Values
Scale (MVS; Richins, 2004a;Richins & Dawson, 1992), which is
widely used in consumer research and psychology. The MVS assesses
the centrality of material goods in a person’s life, as well as beliefs
about improved success and happiness resulting from such acquisi-
tions. The second methodological approach assesses the importance
people place on goals for wealth and possessions. This includes
single- and multiple-item ratings of wealth, income, or money as a
goal, either by itself (Nickerson, Schwarz, Diener, & Kahneman,
2003) or together with closely linked goals (see Grouzet et al., 2005).
A prominent example is the Aspiration Index (AI), which has been
used to measure the goal of financial success (e.g., Kasser & Ryan,
1993) as well as a broader set of materialist, or extrinsic, goals that
include image and fame as well as financial success (e.g., Kasser &
Ryan, 1996). Such goal measures can yield two different types of
materialism assessments: absolute measures, reflecting participants’
ratings of the importance of materialistic goals, or relative measures,
assessing how important materialistic goals are in comparison to a
variety of other types of goal, such as personal relationships, com-
munity involvement, or spirituality. Thus, in both approaches, mea-
sures range from single items purely assessing the significance of
money, wealth, or income to more complex assessments that reflect
multifaceted materialism conceptualizations.
We made two general types of predictions regarding how well-
being would relate to different types of materialism measures. First,
we expected that multifaceted measures, assessing a broader array of
beliefs and goals associated with money and possessions, would be
more strongly related to well-being outcomes than would more simple
measures using an item or two about money and possessions. This
prediction is informed by typical standards for adequate test construc-
tion: Reliable and valid measures sample multiple items from the
universe of possible items relevant to the construct. In addition, we
draw on reviews suggesting that an exclusive focus on the acquisition
of money and possessions alone may not capture the full meaning of
materialism (Dittmar, 2008;Fournier & Richins, 1991;Kasser, 2002).
Our second hypothesis was that those goal measures that use relative
assessments of materialism’s importance to the individual would be
more strongly related to well-being than would those that use absolute
assessments. Our rationale here was that value researchers have long
insisted (Rokeach, 1973) and empirically confirmed (Grouzet et al.,
2005;Maio, Pakizeh, Cheung, & Rees, 2009;Schwartz, 1992) that
any particular value or goal exists within a broader system of values
and goals, so that optimal assessment involves measuring the impor-
tance of a particular goal, such as materialism, relative to other goals
in that system.
Personal Well-Being Measures
The extant literature reveals that materialism is associated with
a wide array of different kinds of well-being. Our review of the
literature led us to create four broad categories of well-being
constructs that have been empirically related to materialism (see
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880 DITTMAR, BOND, HURST, AND KASSER
Table 1
Categorization of Materialism Measures
Category Definition and representative measures
Endorsement of Likert-type scale items
Value of having money and
possessions Definition: Single item or brief measure assessing the value attached to having money and
possessions only.
Representative measures: Single item (Robak, Chiffriller, & Zappone, 2007), important
factor in Money Ethic Scale (Tang, 1992).
Representative items: “How important do you think money will be in your life?”; “I value
money very highly.”
Beliefs related to money and
wealth Definition: A mixture of scales or selected subscales assessing beliefs related to money and
wealth
a
that broadly address status (e.g., power, prestige, achievement, reputation,
popularity).
Representative measures: Achievement, power, respect, and success factors in Love of
Money and Money Ethic Scale (Mitchell & Mickel, 1999;Tang, 1992); Materialism
Scale (Ward & Wackman, 1971); tycoon type in Money Over Mind Questionnaire
(Forman, 1987).
Representative items: “Money represents one’s achievement,” “Money is a symbol of
success,” “People judge others by the things they own.”
Materialist values and beliefs Definition: Scales that assess three interrelated components of materialism—the centrality of
material possessions and wealth in a person’s life, beliefs that they are a good way to
judge the success of self and others, and beliefs that their acquisition increases happiness.
Representative measures: Material Values Scale (Richins, 2004a;Richins & Dawson, 1992),
Youth Materialism Scale (M. E. Goldberg, Gorn, Peracchio, & Bamossy, 2003).
Representative items: “I like a lot of luxury in my life,” “I admire people who own
expensive homes, cars, and clothes,” “I would be happier if I had more money to buy
more things for myself.”
Materialist personality traits Definition: Scales that measure indicators of personality traits and behaviors linked to a
materialist orientation (such as possessiveness, nongenerosity, envy, or accumulating
goods).
Representative measure: Belk Materialism Scale (Belk, 1984; Ger & Belk, 1996).
Representative items: “I worry about people taking my possessions,” “I don’t like to lend
things, even to good friends,” “When friends have things I cannot afford it bothers me.”
Importance ratings
Importance of having money and
possessions (absolute, i.e., by
itself)
Definition: Single- and multiple-item measures of the importance of money, possessions, or
financial success only.
Representative measures: Single item (see Nickerson, Schwarz, Diener, & Kahneman,
2003), financial success in the Aspirations Index scored for absolute importance (Kasser
& Ryan, 1993,1996).
Representative items: “The importance to you personally of being very well off financially,”
“to have many expensive possessions.”
Importance of having money and
possessions (relative, i.e.,
compared to other goals)
Definition: Measures of the strength of financial success relative to intrinsic goals (e.g.,
relationships, community contribution, personal growth).
Representative measures: Financial success in the Aspirations Index (Kasser & Ryan, 1993,
1996) scored for relative importance, relative importance of financial success compared to
four other life goals (Srivastava, Locke, & Bartol, 2001).
Representative items: See above for financial success; intrinsic goals “to have deep enduring
relationships,” “helping others,” “to know and accept who I really am.”
Importance of materialist goals
(absolute, i.e., by themselves) Definition: Importance of a set of goals that include money, income, and material
possessions, as well as closely related goals.
Representative measures: Extrinsic work values (Vansteenkiste et al., 2007); extrinsic work
orientation (Malka & Chatman, 2003); adolescents’ future goals for money, power, and
image (Casas, Gonzales, Figuer, & Coenders, 2004).
Representative items: “Good pay,” “having the material possessions and lifestyle you
desire,” “own image (appearance).”
Importance of materialist goals
(relative, i.e., compared to
other goals)
Definition: Measures of the strength of extrinsic goals (financial success, fame, image)
relative to intrinsic goals (e.g., relationships, community contribution, personal growth).
Representative measures: Financial success, fame, and image in the Aspirations Index
(Kasser & Ryan, 1993,1996;Ryan et al., 1999) scored for relative importance; Guiding
Principles Scale (Kasser & Ryan, 1996).
Representative items: See absolute and relative importance of money above for financial
success and intrinsic goals; “to be admired by lots of different people” (fame), “to keep
up with fashions in hair and clothing” (image).
a
A minority of scales also include items assessing the value of having money and possessions.
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881
MATERIALISM AND WELL-BEING
Table 2). The first category is subjective well-being (SWB; Diener
& Oishi, 2005), which encompasses one’s cognitive appraisals of
overall life satisfaction and satisfaction with different life domains
(Diener, Suh, Lucas, & Smith, 1999), one’s emotional appraisals
of happiness, and the frequency with which one experiences pos-
itive versus negative emotions (i.e., affect balance; Bradburn,
1969). Although these SWB components are theoretically distinct
and can therefore be analyzed separately, they are often examined
as a composite measure, given that they usually positively corre-
late with one another (Diener et al., 1999). The second category
concerns self-appraisals, or individuals’ positive and negative
views of themselves. Positive self-appraisals that have been asso-
ciated with materialism include constructs such as self-esteem
(Ryan et al., 1999), positive self-concept (Lekes, Gingras, Phil-
lippe, Koestner, & Fang, 2010), and self-actualization (Kasser &
Ryan, 1993), which generally involve liking and accepting oneself.
Table 2
Categorization of Well-Being Measures
Category Definition and representative measures
Subjective well-being
Life satisfaction Definition: Measures that assess satisfaction with life overall.
Representative measures: SWLS (Diener, Emmons, Larsen, & Griffin, 1985), 15-item quality of life measure
(Flanagan, 1978), life satisfaction scale for children (Huebner, 1994), Purpose in Life Test (Crumbaugh &
Maholick, 1981), 3-item life satisfaction measure used in U.S. General Social Survey (Easterlin, 2001), single-
item measures of life satisfaction and of happiness.
Negative affect Definition: Measures that assess how much negative affect the individual experiences in his/her life.
Representative measures: PANAS–Negative Affect (D. Watson, Tellegen, & Clark, 1988), negative mood rating,
emotional stability versus neuroticism scale of the Comrey Personality Scales (Comrey, 1987).
Positive affect Definition: Measures that assess how much positive affect the individual experiences in his/her life.
Representative measures: PANAS–Positive Affect (D. Watson et al., 1988), fun and enjoyment (Andrews &
Withey, 1976).
Composite subjective
well-being Definition: Measures that assess an individual’s overall subjective well-being either by a single measure or by
combining measures.
Representative measures: Personal Well-Being Index (Cummins, 1998), Personal Well-Being Scale (Ryff & Keyes,
1995), SWLS and PANAS, SWLS and Affect Balance Scale (Bradburn, 1969), PANAS and Self-Concept Scale
(Anderman, 2002).
Self-appraisals
Positive Definition: Measures that assess positive self-evaluation.
Representative measures: Rosenberg’s Self-Esteem Scale (Rosenberg, 1965), Index of Self-Actualisation (Jones &
Crandall, 1986).
Negative Definition: Measures that assess negative self-evaluation.
Representative measures: Self-Doubt Scale (Oleson, Poehlmann, Yost, Lynch, & Arkin, 2000), Self-Discrepancy
Index (Dittmar, 2005a,2000b), Self-Ambivalence Measure (Bhar & Kyrios, 2007).
DSM Axis 1
Anxiety Definition: Measures that assess anxiety.
Representative measures: State–Trait Anxiety Inventory (Spielberger, Gorsuch, & Lushene, 1970), Hopkins
Symptom Checklist–Anxiety Symptoms (Derogatis, Lipman, Rickels, Uhlenhuth, & Covi, 1974), Beck Anxiety
Inventory (Beck & Steer, 1993), Social Interaction Anxiety Scale (Mattick & Clarke, 1998).
Depression Definition: Measures that assess depression.
Representative measures: Beck Depression Inventory (Beck, Ward, Mendelson, Mock, & Erbaugh, 1961), Center
for Epidemiological Studies–Depression Inventory (Radloff, 1977), Depression scale from Depression Anxiety
Stress Scales (Lovibond & Lovibond, 1995), depression factor from Rubinstein scale (Rubinstein, 1981).
Compulsive buying Definition: Measures that assess propensity to purchase goods excessively.
Representative measures: Compulsive buying scale (Faber & O’Guinn, 1992), Compulsive Buying Scale (D’Astous,
Maltais, & Roberge, 1990), Impulsive Buying Tendency Scale (Verplanken & Herabadi, 2001), 20-item spending
tendency scale (J. J. Watson, 1998).
Other DSM Axis 1 Definition: Measures that assess DSM Axis 1 symptoms other than anxiety, depression, or compulsive buying.
Representative measures: Children’s Global Assessment Scale (Shaffer et al., 1983), Adolescent Community Mental
Health Interview (Ikle, Lipp, Butters, & Ciarlo, 1983), Mental Health Index (Veit & Ware, 1983), Diagnostic
Interview for Children and Adolescents–Oppositional and Conduct Disorders (Herjanic & Reich, 1982),
Internalizing Negative Emotionality Scale (Miller, 2009), Strengths and Difficulties Questionnaire (Goodman,
1997).
Health and physical risk
Physical health Definition: Measures that assess an individual’s overall state of physical health.
Representative measures: Somatic Symptoms Checklist (Klonowicz, 2001), Emmons’s 9-item measure of physical
health (Emmons, 1991), single-item ratings of physical health.
Risk behaviors Definition: Measures that assess the frequency with which the individual uses tobacco, alcohol, or drugs.
Representative measures: Risk Behaviour Index–5 items on tobacco, alcohol, and drug use (Williams, Cox,
Hedberg, & Deci, 2000); Personal Involvement Index–items on alcohol, tobacco, and drug use (Zaichkowsky,
1994); Risky Behavior Questionnaire for Adolescents (Auerbach et al., 2009); single items concerning tobacco,
alcohol, and drug use.
Note.DSM Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; American Psychiatric Association, 2000); PANAS Positive
Affect/Negative Affect Scale; SWLS Satisfaction With Life Scale.
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882 DITTMAR, BOND, HURST, AND KASSER
Negative self-appraisals include constructs such as self-doubt
(Chang & Arkin, 2002), self-ambivalence (R. O. Frost, Kyrios,
McCarthy, & Matthews, 2007), and self-discrepancies (Dittmar,
2005b), which generally reflect dissatisfaction with oneself or a
belief that one is failing to live up to important self-standards. The
third category of well-being constructs includes those that assess
mental ill-health. We focused here on measures relevant to the
Diagnostic and Statistical Manual of Mental Disorder’s (4th ed.,
text rev. [DSM–IV–TR]; American Psychiatric Association, 2000
1
)
Axis 1 emotion-based disorders. Many materialism studies include
assessments of depression and anxiety, two of the most common
types of emotional problems (e.g., Burroughs & Rindfleisch, 2002;
Kasser & Ryan, 1993;Sheldon, 2009;Ryan et al., 1999). A further
disorder of interest to materialism researchers has been compulsive
buying, which entails a dysfunctional relationship to consumer
goods characterized by loss of control over buying behavior,
preoccupation with thoughts about buying, and the continuation of
excessive buying and spending despite harmful consequences (Dit-
tmar, 2004,2005a,2005b;R.O.Frost et al., 2007;Roberts &
Manolis, 2012). We also included in this third category other DSM
Axis 1 measures that concern general levels of psychopathology
and mental health functioning not specific to any particular DSM
disorder. Our fourth category reflects measures relevant to one’s
physical health. These include assessments of different somatic
symptoms, such as headaches and stomachaches, as well as mea-
sures of how often individuals engage in different types of health
risk behaviors, such as smoking cigarettes, drinking alcohol, or
using drugs (P. Cohen & Cohen, 1996;Vansteenkiste, Duriez,
Simons, & Soenens, 2006;Williams, Cox, Hedberg, & Deci,
2000).
In contrast to our hypotheses regarding how strongly different
materialism measures would relate to well-being, we made no
specific hypotheses about how strongly different well-being mea-
sures would relate to materialism. To our knowledge, no theoret-
ical statements have been made that would suggest reasons for
expecting materialism to relate more strongly to one type of
well-being outcome than to another. Instead, most of the theoret-
ical explanations for the negative relationships between material-
ism and well-being postulate processes that would likely result in
lowered levels of well-being across a broad band of outcomes.
Consider three different explanations, none of which are mutually
exclusive.
One account suggests that materialism leads to negative self-
appraisals in response to advertising and consumer culture mes-
sages that emphasize material wealth (Dittmar, 2008;Richins,
1991;Sirgy, 1998). When people oriented toward money, expen-
sive goods, and image attend to the advertising messages in con-
sumer culture, they are frequently exposed to messages suggesting
that they are insufficient in one way or another. This can lead both
to negative self-evaluations resulting from upward social compar-
isons (Collins, 1996;Richins, 1994) and to increased discrepancies
between one’s current and ideal selves (Halliwell & Dittmar, 2006;
E. T. Higgins, 1987). For example, one experimental study found
that, compared to less materialistic women, women with strong
materialistic values reported larger self-discrepancies after view-
ing advertisements containing models with expensive goods
(Ashikali & Dittmar, 2012). In turn, self-discrepancies have been
linked empirically to negative affect and symptoms of depression
and anxiety (E. T. Higgins, 1987) and identified alongside mate-
rialism as a predictor of excessive buying of consumer goods
(Dittmar, 2005a). Furthermore, some people may express these
unpleasant states via somatic means or try to cope with low mood
and self-discrepancies through self-medication efforts, such as the
use of alcohol and drugs, or excessive buying and spending (Ben-
son, 2000). Thus, if materialism makes people vulnerable to neg-
ative self-appraisals in response to advertising messages, which
can express themselves in different types of lowered personal
well-being, then it is plausible that materialism is associated with
a wide range of well-being outcomes.
A second account suggests that materialism is symptomatic of
an underlying feeling of psychological insecurity (Kasser, 2002).
Studies show that people who grow up with cold, controlling
mothers (Kasser, Ryan, Zax, & Sameroff, 1995), whose parents
divorce (Rindfleisch, Burroughs, & Denton, 1997), or who were
raised in economically difficult situations (Kasser et al., 1995) tend
to place a higher value on materialism. Additionally, experimental
studies show that manipulations of self-doubt and uncertainty
(Chang & Arkin, 2002), of mortality salience (Kasser & Sheldon,
2000), and of relational and economic insecurity (Sheldon &
Kasser, 2008) each lead to an increased focus on materialistic
strivings. Thus, if materialism is a type of culturally sanctioned
coping strategy that some people use in order to attempt to deal
with their feelings of insecurity (Kasser, Ryan, Couchman, &
Sheldon, 2004) and if feelings of insecurity reflect themselves via
diverse types of well-being (including anxiety, lowered life satis-
faction, and less happiness), then we would again expect that
materialism is related to a broad array of well-being outcomes.
A third account, derived from self-determination theory (SDT),
suggests that the pursuit of materialistic values and goals leads
individuals to create a lifestyle and to have experiences that crowd
out other, more satisfying experiences in life, thereby undermining
the satisfaction of psychological needs that are essential for psy-
chological thriving (Deci & Ryan, 2000;Kasser, 2002). Indeed,
data show that high levels of materialism are associated with
relatively poor satisfaction of psychological needs for competence,
autonomy, and relatedness (Kasser, 2002) and that such associa-
tions account empirically for the negative relations between ma-
terialism and well-being (Kasser et al., 2014;Niemiec et al., 2009).
Thus, if materialism interferes with one’s sense of being an effi-
cacious person, having choices in one’s life, and enjoying high
quality interpersonal relationships, we would again predict that
materialism relates negatively to a broad array of well-being
outcomes.
Thus, our hypothesis was that materialism would relate nega-
tively to a variety of types of well-being constructs. We remained
interested, however, in whether some types of well-being would be
more closely related to materialism than others.
Does the Negative Relationship Depend on
Characteristics of the Participants?
Enough variation exists in the demographic characteristics of
samples in this meta-analysis to allow us to test whether such
1
Our categorization scheme was informed by this version of the DSM,
rather than the new, fifth, version published in 2013.
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883
MATERIALISM AND WELL-BEING
characteristics affect the size of the association between material-
ism and well-being. Although, to our knowledge, there is little by
way of single studies suggesting such effects, one study found
relatively weak associations between materialism and well-being
in subsamples of Russian females (Ryan et al., 1999). We therefore
examined whether age, gender, ethnicity, and education moderate
the link between materialism and well-being but made no specific
hypotheses.
Clear debate does exist, however, about whether the association
between materialism and well-being is moderated by two other
demographic factors: participants’ professional expertise and in-
come. Regarding professional expertise, power and achievement
values have been found to be associated positively with SWB
among Israeli business students, but not among psychology stu-
dents (Sagiv & Schwartz, 2000). These findings have been inter-
preted as consistent with a person–environment value congruence
hypothesis, which holds that SWB is enhanced when a person’s
values match the dominant priorities of the surrounding environ-
ment because such a match provides opportunities to express one’s
values, diminishes the frequency of receiving external sanctions
due to failures to conform, and reduces the experience of internal
conflict that might arise from value incongruence. In contrast,
other studies that assessed materialism directly, rather than via
power and achievement values, found that negative associations
between materialism and well-being also occur among business
students and entrepreneurs (e.g., Kasser & Ahuvia, 2002;Srivas-
tava, Locke, & Bartol, 2001;Vansteenkiste et al., 2006). These
latter results suggest that materialism is problematic for people’s
well-being even when their professional environment supports
goals for profit making. Such results are also consistent with SDT
accounts reviewed above (Deci & Ryan, 2004;Kasser, 2002),
which suggest that the pursuit of materialistic aims undermines the
satisfaction of the psychological needs necessary for the well-
being of any person, regardless of his or her profession or area of
study. In the current meta-analysis, we therefore coded the pro-
portion of individuals in each sample who were studying or prac-
ticing a profession that could be understood as supportive of
materialistic ambitions; doing so allowed us to explore this demo-
graphic factor as a potential moderator.
Competing hypotheses can also be derived concerning the pos-
sibility of moderation by personal income. First, materialism may
not be so detrimental for well-being if one is wealthy. Such a
hypothesis seems consistent with cognitive-behavioral and goal-
attainment approaches (e.g., Bandura, 1977;Locke & Latham,
1990;Oishi, Diener, Lucas, & Suh, 1999;Seligman, 1991), which
propose that well-being improves when one attains rewards and
fulfils the goals one has set. As such, people of a relatively high
income would be in a better position to fulfil their material desires
than would poorer individuals. Some evidence supports this view-
point among U.S. (Nickerson et al., 2003) and Icelandic (Garðars-
dóttir, 2006) adults. Second, materialism may not be so detrimental
for well-being if one is poor. Such a hypothesis seems consistent
with Maslovian perspectives (Maslow, 1954) suggesting that needs
for safety and security must be satisfied (perhaps through materi-
alistic goals) before one can focus on other, higher level needs.
Research does show that economic stress increases one’s focus on
financial success goals (P. Cohen & Cohen, 1996;Kasser et al.,
1995;Sheldon & Kasser, 1998) and shifts the meaning of mate-
rialistic goals, making money more akin to issues of health and
safety than to popularity and image (Grouzet et al., 2005). There-
fore, for poorer people, materialistic strivings may concern the
satisfaction of basic deficiency needs (see also Bilsky & Schwartz,
1994), and thus, a strong focus on them may not be as damaging
as it is for wealthier people, for whom materialism is about more
superficial, extrinsic (Kasser & Ryan, 1996) concerns. One study
that supports this possibility reported a negative relationship for
Japanese and U.S. respondents, but not for Thai respondents (i.e.,
those in a poorer, developing economy; Wong et al., 2003). A third
possibility would suggest no moderation by income. Such a hy-
pothesis would be consistent with SDT (Deci & Ryan, 2000),
which, again, suggests that well-being depends largely on the
satisfaction of needs for autonomy, competence, and relatedness:
Thus, wealthy and poor alike would have diminished well-being to
the extent that they focus on materialism. Some evidence supports
this viewpoint, as no interaction between wealth and income was
detected in a relatively heterogeneous sample of U.S. adults
(Kasser & Ryan, 1996). Given these mixed results, this meta-
analysis coded the actual wealth of participants, when available, in
order to examine its potential moderating influence on the rela-
tionship between materialism and well-being.
Does the Negative Relationship Depend on
Characteristics of the Participants’ Society?
As noted above, studies examining the associations between
materialism and well-being have been conducted in a relatively
wide array of nations. This allowed us to examine whether various
economic and cultural characteristics of the society participants
live in affect the size and direction of the relation between mate-
rialism and well-being.
Economic Indicators
Economic conditions and organization of countries seem to hold
particular potential as moderators, given their special relevance to
the variable of materialism. We examined three types of economic
indicators.
First, to ascertain an overall sense of the economic wealth of a
nation, we obtained data on its gross domestic product (GDP) per
capita and its annual growth in GDP.
2
Countries with relatively
high levels of material deprivation would be likely to lead mate-
rialistic individuals to experience high levels of frustration of their
desires, whereas wealthy nations with high economic growth
would provide numerous opportunities to fulfil one’s materialistic
goals. Thus, one hypothesis consistent with a goal-attainment
perspective is that the negative association of materialism and
well-being may be smaller (or nonexistent) among those living in
a more affluent country than those living in a less affluent country.
On the other hand, individuals in wealthy mass-consumer societies
are more frequently exposed to consumer culture messages profil-
ing materialistic values and goals; according to the consumer
culture values impact model (Dittmar et al., 2013), this is likely to
2
There is a substantial literature on the relationship between country
wealth and well-being, which shows that individuals in richer countries
report higher well-being (e.g., Diener, Diener, & Diener, 1995). Here we
are concerned only with country wealth as a potential moderator of the
materialism-well-being link.
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884 DITTMAR, BOND, HURST, AND KASSER
create frequent self-discrepancies of the kinds described above
(see Dittmar, 2007,2008). As also noted above, goals for financial
success may have a different psychological meaning in poorer
nations, being connected with safety and health more strongly than
with image and status (Grouzet et al., 2005). Such reflections
would suggest that the negative association of materialism and
well-being may be smaller (or nonexistent) among those living in
a less affluent country than those living in a more affluent country.
A second set of indicators concerns the distribution of wealth in
a country, rather than level of wealth per se. Greater income
inequalities, measured by the GINI index (World Bank, n.d.),
appear to be associated with many social and personal costs
(Wilkinson & Pickett, 2009) and would be likely to make status
differences, unequal opportunities, and social comparisons with
the wealth of others particularly salient to individuals who prior-
itize materialistic aims. For these reasons, a materialistic orienta-
tion may be particularly problematic for the well-being of individ-
uals who live in countries with greater income inequalities, given
that in such nations, far more individuals tend to be at the bottom
of the pyramid than at the top. However, recent research (Ord-
abayeva & Chandon, 2011) suggests that two different processes
may be at work when bottom-tier consumers find themselves in a
context characterized by inequality of material possessions or
income: While a focus on social comparison processes and greater
perceived possession gaps may decrease satisfaction, a focus on
the reduced opportunities for actual position gains derived from
status-enhancing consumption may have the opposite effect.
The third set of economic indicators concerns the economic
organization of a country. Some nations have more regulated
economic systems in which the government is involved in man-
aging the economy and influencing the decisions and options
available to consumers, laborers, and the private sector, whereas
other nations follow a more free-market approach in which such
decisions are turned over to the invisible hand of competition
among these players, with little interference from government
(Hall & Gingerich, 2004). Past research suggests that values for
money, power, achievement, and status tend to be higher among
citizens living in nations that organize their economies in more
deregulated, free-market ways (Kasser, 2011a;Schwartz, 2007).
Thus, it would seem that predictions derived from goal-attainment
and person–environment value congruence perspectives would
suggest that materialism’s negative association with well-being
would be diminished in nations whose economies are particularly
deregulated (see, e.g., Locke, 2007), as such individuals would
experience fewer roadblocks in their attempts to maximize profits
and acquire possessions. On the other hand, living in such dereg-
ulated economic environments may lead to greater internalization
of materialistic values, accompanied by a greater suppression of
other, healthier, intrinsic values (see Kasser, Cohn, Kanner, &
Ryan, 2007). As such, materialism may be more strongly nega-
tively related to people’s well-being in such nations.
Cultural Values
Just as individuals have values and goals, psychologists and
others have conceived of values as existing also at the cultural
level (Hofstede, 2001;Schwartz, 1999;P.B.Smith & Schwartz,
1997). Such approaches assess the extent to which citizens in a
nation care about certain sets of aims and then aggregate individual
data to obtain estimates reflecting a particular nation’s orientation
toward particular values. We examine eight such cultural values as
potential moderators of the relationship between well-being and
materialism. The first concerns how much citizens in different
countries prize the acquisition of money and possessions (World
Values Survey, 2005), thereby giving some indication of a society-
level endorsement of materialist values. The other seven were
derived from the substantial cross-cultural research of Schwartz
(1999,2006; see also Ralston et al., 2011) and included harmony
(unity with nature and a world at peace), embeddedness (social
relationships, ingroup solidarity, and emphasis on group goals),
hierarchy (status differentiation, authority, and obligations), mas-
tery (personal goals and dynamic self-assertion), affective auton-
omy (pursuit of pleasure and an exciting life), intellectual auton-
omy (independent pursuit of one’s own ideas and intellectual
directions), and, last, egalitarianism (social justice and equality).
Schwartz (2007) found that nations with more neo-liberal, free-
market economic organizations also tend to prioritize hierarchy,
mastery, and embeddedness values and place less focus on har-
mony, egalitarianism, and intellectual autonomy values. Thus,
following this logic, an environmental congruence hypothesis
would suggest that materialism’s negative association with well-
being should be relatively diminished in nations more focused on
materialism, mastery, and hierarchy, given the relative support
such cultural values would provide for a personal focus on mate-
rialism. On the other hand, as suggested above, to the extent such
values are dominant in one’s society, they may make the pursuit of
materialistic values all the worse for well-being by diminishing
people’s need satisfaction.
What Is the Process Through Which Materialism
Relates to Lower Well-Being?
A final, more exploratory issue we addressed concerns media-
tional variables that may explain the negative association between
materialism and well-being. We consider these analyses explor-
atory because relatively few studies have examined such media-
tional processes and because some potential explanations have not
received sufficient empirical attention so they could not be in-
cluded in this set of analyses for comparative purposes.
Despite these limitations, sufficient data were available to ex-
plore two mediational hypotheses. The first, described earlier,
derives from SDT (Deci & Ryan, 2000;Kasser, 2002), which
suggests that people who prioritize materialistic aims experience
lower satisfaction of their needs for autonomy, competence, and
relatedness because their concerns with money, possessions, and
image crowd out pursuits likely to lead to greater well-being in the
long run; this low need satisfaction thus accounts for the lower
well-being reported by materialistic individuals. The second ap-
proach (e.g., Sirgy, 1998) suggests that people who prioritize
materialistic aims experience lower satisfaction in the financial
realm of their lives, given that one can always make more money
or have nicer possessions and given that there is usually someone
wealthier to whom one can upwardly compare. This low financial
satisfaction is then thought to spill over into satisfaction with other
domains of one’s life, thereby diminishing well-being more gen-
erally. This type of approach, sometimes called the escalation
hypothesis, encompasses further mechanisms, in addition to finan-
cial satisfaction, such as acclimatization and the hedonic treadmill,
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885
MATERIALISM AND WELL-BEING
where the thrill of buying and owning new things wears off
quickly and larger and more frequent purchases become necessary
to appease materialists’ appetite for positive stimulation through
acquisition (Dunn, Gilbert, & Wilson, 2011). However, sufficient
studies were available only to test the financial satisfaction com-
ponent.
Summary
This meta-analysis addresses numerous questions about the as-
sociation between materialism and personal well-being. We aim to
establish an estimate of the size and direction of the association
between materialism and well-being, both with and without cor-
recting for the reliability of measures. We examine whether the
magnitude of the association depends on particular features of how
materialism is assessed, expecting that multifaceted measures and
relative assessments of materialistic values yield stronger associ-
ations than less complex measures or absolute assessments of
materialistic values. We expect that materialism relates negatively
to a wide array of well-being outcomes but are interested in
potential variation in the size of such associations. We seek to
determine whether person-level and society-level variables mod-
erate the size of the association between materialism and well-
being, so as to test competing hypotheses about the conditions
under which this relationship may obtain. Finally, we conduct
exploratory analyses to examine two proposed mediators of the
negative relationship between materialism and well-being.
Method
Literature Search and Inclusion Criteria
We used four strategies to locate reports of relevant studies.
First, we searched the online databases PsycINFO, Web of Knowl-
edge, and Index to Theses by pairing a set of materialism search
terms with a set of well-being search terms. The Boolean OR
operator was used for terms within a set, and the AND operator
was used for terms between the two sets. Examples of materialism
search terms are materialism, material values, and financial suc-
cess, and examples of well-being search terms are happiness,
well-being, and life satisfaction (see the Appendix for a full list of
sets of search terms). Second, we conducted ancestor searches by
scrutinizing the reference lists of review articles and reports we
had located. Third, we carried out a descendancy search by check-
ing for articles citing key papers
3
in the area (e.g., Kasser & Ryan,
1993;Richins & Dawson, 1992) using Web of Knowledge. Fourth,
we wrote to 20 researchers who are well published in the materi-
alism area, requesting that they provide us with any unpublished
work they had conducted concerning materialism and well-being.
We included work reported in any language. Databases were
searched up to June 1, 2013.
Initially, we included not only correlational but also experimen-
tal and longitudinal studies in our search. Due to the small number
of noncorrelational studies, experimental reports
4
were excluded,
as were studies using implicit measures.
5
For the few longitudinal
studies we identified,
6
only correlations reported at the first data
collection point were included so as to maintain comparability
with other samples. We return to these research gaps, as well as the
paucity of research on children under 12 years, in the Discussion.
In order to be included in this meta-analysis, the report or data
set had to include at least one study in which there were measures
of both materialism and well-being and in which the zero-order
correlation between these measures either was reported directly,
could be obtained (from authors), or could be derived (see
Lipsey & Wilson, 2001). Given that this meta-analysis defines
materialism as individual differences in people’s long-term en-
dorsement of values, goals, and associated beliefs that center on
the importance of acquiring money and possessions that convey
status, we excluded studies examining beliefs about philosophical
materialism or the goals a society should pursue, attitudes to
budgeting money or material purchases, or values for power (as
detailed in the introduction). Regarding well-being measures, we
included assessments of (a) SWB (e.g., life satisfaction, positive
and negative emotions), (b) positive or negative self-appraisals
(e.g., self-esteem, self-discrepancies), (c) constructs relevant to
DSM Axis 1 disorders (e.g., anxiety, depression, compulsive buy-
ing), and (d) indicators of physical health and health risk behaviors
(e.g., somatic symptoms; substance misuse).
7
Further details are
given below under Coding of Materialism and Well-Being Mea-
sures.
As shown in Figure 1, our database searches generated 1,380
reports. We rejected 1,049 on a reading of the abstracts and rejected
a further 195 on a close reading of the report, resulting in 136 eligible
reports. We wrote to 12 authors for additional data (typically because
zero-order correlations had not been reported), and five authors re-
sponded; 17 of the studies we obtained from this process were
excluded because appropriate statistics were not available. In addition,
four of the 20 researchers whom we contacted responded with un-
published data, yielding a further 32 studies. Thus, 151 reports met
our eligibility criteria.
Coding of Studies
For each report, we coded (a) type of publication (e.g., book,
journal article, thesis) and (b) year of publication. For each study, we
3
The top 10 cited articles on the correlational link between materialism
and well-being over the past 30 years that fit our definition of a material-
istic value orientation are Belk (1984);Burroughs and Rindfleisch (2002);
Kasser and Ryan (1993,1996); Ryan et al. (1999);Richins (2004a);
Richins and Dawson (1992);Rindfleisch, Burroughs, and Denton (1997);
Sirgy (1998); and Srivastava, Locke, and Bartol (2001).
4
A small number of experiments manipulated materialism and observed
the impact on well-being (Bauer, Wilkie, Kim, & Bodenhausen, 2012;
Kasser et al., 2014) or manipulated aspects of well-being and observed the
impact on state materialism (Chang & Arkin, 2002;Chaplin & John, 2007;
Sheldon & Kasser, 2008;Lambert, Fincham, Stillman, & Dean, 2009;
Solberg, Diener, & Robinson, 2004). A separate, small-scale meta-analysis
on these experimental effects is underway (Moldes, Dittmar, Bond,
Hurst, & Kasser, 2014).
5
One study involved an adaptation of the implicit association test
(Solberg et al., 2004), one used reaction times (Schmuck, 2001), and
another two entailed collages later coded for materialistic themes
(Chaplin & John, 2007;Park & John, 2010). All reported moderate to
strong correlations between materialism and well-being.
6
These are Auerbach et al. (2009,2011),Kasser et al. (2014),Malka and
Chatman (2003),Nickerson et al. (2003),Niemiec et al. (2009), and
Sheldon (2005a,2009).
7
Our search also included other areas of well-being—interpersonal,
financial, performance, and environmental (Hurst, Dittmar, Bond, &
Kasser, 2013)—and the search terms used are detailed in the Appendix.
The results of these additional searches are not considered in this article.
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886 DITTMAR, BOND, HURST, AND KASSER
recorded type of data collection method (e.g., questionnaire, face-to-
face interview, telephone interview). For each independent sample,
we recorded (a) sample size, (b) country in which data were collected,
(c) percent female respondents, (d) mean age (or age range), (e)
average income, (f) percent White, (g) percent who did not complete
high school or the national equivalent, (h) percent in higher education,
and (i) percent of respondents who study a subject or work in an
occupation that is supportive of materialism (i.e., business, marketing,
or economics).
We included in this meta-analysis each correlation between a
measure of materialism and a measure of well-being for each
independent sample reported. When necessary, correlations were
reverse-scored so that a negative correlation always indicated that
higher materialism was associated with lower well-being. For each
effect size, we also recorded (a) type of materialism measure, (b)
type of well-being measure, (c) reliability of materialism measure,
and (d) reliability of well-being measure.
Coding of Materialism and Well-Being Measures
In addition to the primary coding, we coded measures of materi-
alism and measures of well-being into broader categories. The initial
143 distinct measures of materialism were grouped into eight catego-
ries, four using Likert-type scales and four using importance ratings
(see Table 1). The initial 497 distinct measures of personal well-being
were grouped into 12 categories, falling into four overarching cate-
gories: SWB, self-appraisals, DSM Axis 1, and health and physical
risk (see Table 2).
To check the reliability of our coding procedure, a 20% sub-
sample of all reports (selected according to a random number
generator) was coded by two independent raters. With respect to
all factual information, such as recording the year of publication or
data collection method, no disagreements occurred. For the mate-
rialism and well-being measures, we coded both overarching cat-
egories and main categories and then calculated interrater reliabil-
ity coefficients, weighted for severity of disagreement (J. Cohen,
1968).
8
The central findings for materialism were that raters ob-
tained perfect agreement when coding measures, so that k
w
1.00
for agreement about both the broad method used for materialism
measures (Likert-scale or importance rating) and the specific cat-
egory (e.g., materialist values and beliefs, importance of materi-
alist goals [relative]). With respect to well-being measures, inter-
rater reliability was equally excellent, again for both the four broad
categories and the 12 categories of outcomes (k
w
1.00).
Coding of Additional Variables
We also derived from, or added to, the primary coding several other
variables to test as potential moderators. From the type of publication,
we coded whether the report was published or unpublished.
9
In terms
of participant characteristics, we coded the proportion of individuals
in each sample working in a profession or studying a subject likely to
support materialist values (such as business or marketing). For eco-
nomic variables, such as income, it is important to ensure that mea-
sures are comparable across different countries and different years. As
such, personal income and household income for countries other than
the United States were converted to U.S. dollars using purchasing
power parity data for the year in which a study was conducted (World
Bank, n.d.); these values were then converted to 2005 prices (the
median publication year for the sample) using the GDP Deflator
(World Bank, n.d.).
We coded a number of economic characteristics of the country in
which a study was conducted: (a) GDP per capita, converted as just
described; (b) GDP percentage growth (World Bank, n.d.); and (c) the
GINI coefficient, a measure of income inequality (World Bank, n.d.).
We also recorded the Economic Freedom Index (Heritage Founda-
tion, 2011), a measure that averages numerous components of eco-
nomic freedom, such as freedom of trade and investment, tax burden,
and government expenditure. Finally, we used two sources to char-
acterize the prevailing cultural values in a country. The first was a
measure of how much the acquisition of personal wealth is valued,
where we used a country’s citizens’ mean agreement with the state-
ment that it is important for a person to be rich and have a lot of
money and expensive things (World Values Survey, 2005). Second,
we drew on the work of Schwartz (1992,1999,2007), coding each
country’s scores on the cultural values of harmony, hierarchy, em-
8
Disagreements between overarching categories were double-weighted
compared to disagreements within an overarching category. Disagreements
were also recorded in terms of the individual measures, such as the nine-,
15-, or 18-item version of the MVS, yielding less than 2% of disagree-
ments.
9
Journal articles, books, and book chapters were coded as published,
whereas conference papers and dissertations, as well as unpublished man-
uscripts and data sets, were coded as unpublished.
Records identified from
database searches
(n = 1380)
Records identified from other
sources
(n = 32)
Records screened
(n = 1412)
Records excluded
(n = 1244)
Reports eligible for inclusion
(n = 168)
Studies where data unavailable
(n = 17)
Reports included
(n = 151)
Figure 1. Literature search diagram. This diagram was constructed ac-
cording to American Psychological Association Meta-Analysis Reporting
Standards (MARS).
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887
MATERIALISM AND WELL-BEING
beddedness, mastery, affective autonomy, intellectual autonomy, and
egalitarianism.
10
Data Analysis Overview
We used the Hedges-Olkin method (Borenstein, Hedges, Higgins,
& Rothstein, 2009;Shadish & Haddock, 2009) for the meta-analysis,
in which correlations are transformed to Fisher’s zto stabilize the
variance, and followed Hafdahl’s (2009,2010;Hafdahl & Williams,
2009) recommendation to use an integral z-to-rtransformation for
converting our results back to the rmetric. We decided to fit random-
effects models, treating our studies as a sample from a wider popu-
lation, using a restricted maximum-likelihood estimator (Viechtbauer,
2005) and adjustment to standard errors (Knapp & Hartung, 2003).
We report both effect sizes that are not (r) and are () corrected for the
reliabilities of the measurement scales used (Borenstein et al.,
2009).
11
A number of reports contained multiple effect sizes, partic-
ularly those that measured more than one well-being outcome, and we
used methods of elimination and aggregation to ensure independent
effect sizes (details of which are given when analyses are described in
Results). Unless indicated otherwise, all analyses used the metafor
package (Viechtbauer, 2010), within the R statistical computing en-
vironment (R Core Team, 2013).
Results
Description of Data Set
In total, we used 151 reports that included 175 separate studies
12
that, in turn, provided 258 samples.
13
Characteristics of these 258
samples are given in Table 3. In terms of the type of report included,
it can be seen that 32% (83 of the 258 samples) came from unpub-
lished sources, a high percentage. Thus, we were successful in sam-
pling the grey literature (Rothstein & Hopewell, 2009), thereby in-
creasing our confidence that the results are not affected unduly by
publication bias (see Ferguson & Brannick, 2012;Rothstein & Bush-
man, 2012; see also final section of Results). Information about year
of publication indicates how much the materialism and well-being
literature has burgeoned as a research topic since 2000, with the
overwhelming majority of reports (90%) published between 2000 and
2013. Data are mostly derived from questionnaires administered with
the researcher present (57%), and the reliability of both materialism
and well-being measures exceeds .80 on average. Median sample size
is just over 200, with slightly more female than male participants
(median proportion female 57%) and predominantly participants of
White ethnicity (85%). Median age is 24 years, and the large majority
of reports (86%) use adult samples, with just over half of these being
students in higher education. We found that just over a third of the
reports used participants studying or working in economics, business,
or marketing (when such information was reported). Details of par-
ticipants’ annual personal income or household income were only
provided for a few samples; average personal income was just over
$30,000 per annum, and household income was $52,000 per annum
(after adjustments described in the Method section). With respect to
country of data collection, we were able to include studies from every
populated continent, although half of all studies were carried out in
North America.
Size and Direction of the Correlation Between
Materialism and Well-Being
Effect-level meta-analysis. From these 258 samples, we coded
a total of 749 effects, that is, correlations between a measure of
materialism and a measure of well-being. When graphed, the different
sizes of the correlations across these 749 effects reveal an approxi-
mately normal distribution (skewness 0.10, SE 0.09; kurtosis
1.25, SE 0.18). The mean size of the correlation between materi-
alism and well-being ⫽⫺.15, the median ⫽⫺.15, the 25th percen-
tile ⫽⫺.24, and the 75th percentile⫽⫺.05. When we correct the
correlation for the reliability of the measures, the average effect is
somewhat larger, M⫽⫺.19. Thus, taken over a wide range of
different measures of well-being and of materialism, we found a
modest but definite negative relationship between materialism and
well-being. In short, the more strongly individuals endorse material-
istic values, the poorer their personal well-being.
Sample-level meta-analysis. The effect-level analysis just re-
ported suffers from the problem of nonindependence of effects, given
that a number of correlates of materialism were often reported for a
single sample. Thus, it is necessary to conduct analyses choosing a single
effect from each sample. We used both aggregation and elimination
strategies whenever more than one correlation was available for a sample
to obtain one single correlation for each sample between a measure of
materialism and one of well-being (see later sections for details).
Within a particular study, multiple materialism measures were
quite rare, whereas multiple well-being measures were more com-
mon. To choose the materialism measure, we used an elimination
strategy; specifically, where possible, we selected a version of
either the MVS (Richins, 2004a;Richins & Dawson, 1992)orthe
AI (Kasser & Ryan, 1996), as these two measures each have strong
psychometric properties, have been widely validated, and have
strong theoretical rationales for their construction. Thus, whenever
either the MVS or AI was among those materialism measures used
in the sample, an effect for that measure was selected.
14
For each sample that reported an effect with more than one measure
of personal well-being, we used a combination of elimination and
aggregation strategies. When a sample had more than one of the 12
10
We are grateful to Shalom Schwartz (personal communication, Feb-
ruary 28, 2011) for providing country scores on each of these value
dimensions based on data gathered with the 56–57 item Schwartz value
survey between 1988 and 2007.
11
Reliabilities are reported for about half of the data sets; for the other
half, we imputed, where available, reliability coefficients based on those
reported in the literature. For single-item measures, we imputed .57 (see
Wanous, Reichers, & Hudy, 1997).
12
One hundred twenty-nine reports involved one study, 16 involved
two, five involved three, and one involved five.
13
One hundred thirty-nine studies produced one sample, 23 produced
two samples, six produced three samples, 11 produced four samples, one
produced five samples, and one produced six samples.
14
For 10 samples, we selected effects involving the MVS over other
materialism measures; for five samples, we chose the AI. Seven samples
included both measures, and here, we selected randomly. Four samples
with multiple materialism measures did not include either the MVS or the
AI: for two, we selected a money-related belief measure, and for the other
two, we chose absolute importance of money ratings. Eighteen samples had
more than one materialism measure that fell into the same category; here,
we selected the measure we judged best represented the category. The
deletion of effects when samples had multiple materialism measures re-
duced the total number of effects from 749 to 604.
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888 DITTMAR, BOND, HURST, AND KASSER
types of well-being outcome described in Table 2, our criterion for
selection was to choose whichever outcome had the smallest fre-
quency of effects, so as to ensure that each type of well-being
outcome was well represented in our meta-analysis; in this way, we
protected those types of outcomes that were less frequently observed
in our sample of studies. We used aggregation when a sample had
several measures of outcomes within the same category (e.g., several
measures of life satisfaction).
Table 4 gives details of the effect sizes and characteristics of the
resulting 258 independent samples that were retained after selecting
the materialism and well-being measures using the criteria just de-
scribed; those effect sizes that were aggregated are listed separately,
together with the category of materialism or well-being measure. For
the final set of independent effect sizes, we obtained a mean effect
size of .15, with a 95% confidence interval (CI) from .18 to .13.
The narrow width of this interval, especially given the greater strin-
gency of this analysis, helps to increase our confidence that materi-
alism is indeed linked to significantly lower personal well-being.
When examining the extent to which effect sizes vary, the test for
heterogeneity proved highly significant (Q
E
4,114.36, df 257,
p.001); furthermore, the I
2
statistic (J. P. T. Higgins & Thompson,
2002), which quantifies the proportion of total variability that is
estimated as arising from variability in the population effects (as
distinct from sampling error, the other source of variability), is
94.62%, indicating that variability in effect size is substantial and the
major source of variation in the data. Corresponding results for the
analysis of these 258 correlations after correcting for reliability are
somewhat stronger (␳⫽⫺.19, 95% CI [.21, .17], Q
E
4,092.03,
df 257, p.001, I
2
94.02%). The 80% credibility interval for
, ranging from .45 to .10, is also indicative of the wide range in
effect sizes.
In sum, overall, there is a significant but modest negative relationship
between materialism and personal well-being, but there is also consider-
able heterogeneity in the size of this negative relationship. Thus, it
becomes crucial to investigate factors that may moderate the size of this
effect, and it is this issue that we address in the following sections.
Testing Moderation by Type of Materialism
and Well-Being Measure
We first examined whether the type of materialism measure and the
type of well-being measure used by researchers moderate the size of
the relationship between materialism and well-being reported in our
258 independent samples. We did so by conducting an analysis in
which factors representing the eight types of materialism measures
and the 12 types of well-being measures were included in the model,
thereby allowing us to examine the effect of one factor while con-
trolling for the other and vice versa.
15
The analysis shows that both
the type of materialism measure, F(7, 237) 3.45, p.001, and the
15
Our first step was to examine outliers, computing several indices of how
much each study deviated from the average, and look at the effect of deleting
that study on the results (Viechtbauer & Cheung, 2010). Two studies reported
significant positive relationships between materialism and well-being (Izdenc-
zyova, 2009;Wong et al., 2003, Thailand sample), had large studentized
residuals (2.40 and 4.70, respectively), and had other influence statistics that
exceeded thresholds suggested by Viechtbauer and Cheung (2010).Wede-
cided, therefore, to eliminate these two samples and base our remaining
analyses on 256 samples.
Table 3
Sample Characteristics (k 258 Unless Otherwise Indicated)
Characteristic n
Report characteristics
Type of publication
Journal article 165
Book chapter 9
Conference paper 1
Unpublished paper 21
Dissertation 31
Data set 31
Year of publication
1980–1989 1
1990–1999 25
2000–2009 179
2010–2013 53
Study characteristics
Design
Correlational 235
Comparison of intact groups 5
Longitudinal 18
Data collection method
Questionnaire—researcher present 146
Face-to-face interview 17
Postal questionnaire 72
Online survey 23
Sample size
Mdn 207
Range: 25–10,907
Reliability of materialism measure
Mdn .81
Range: .30–.93
Reliability of well-being measure
Mdn .85
Range: .45–.95
Participant characteristics
Proportion female (k230)
Mdn .57
Average age (k176)
Mdn 24
Range: 10–75
Age group
18 years and under 31
Over 18 years 222
Both over and under 18 5
Proportion White ethnicity (k59)
Mdn 85.0%
Range: 24.4%–100%
Whether in higher education
All in higher education 129
General population 95
Under 18 years old 34
Proportion studying business, economics, or
marketing (k39)
None 23
Half 2
All 14
Personal income U.S.$ (k27)
Mdn $30.4k
Range: $3.4k–$80.0k
Household income U.S.$ (k19)
Mdn $52.0k
Range: $0.5k–$290k
Region in which study conducted
North America 129
South America 4
Western Europe 55
Southern Europe 10
Eastern Europe 19
Asia 21
Middle East 4
Australasia 10
Africa 1
Worldwide 5
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889
MATERIALISM AND WELL-BEING
Table 4
Studies Included in the Meta-Analysis: Effect Sizes and Study Characteristics
Study N
a
r
b
Materialism
measure Outcome
measure Type of
publication Country %
female Average age/age
group (years) Population
Average income/
educational
background % White
Agarwal (2003) 240 .14 .18 Money SWLS Journal article India 48 Over 18 Student
Auerbach, McWhinnie,
Goldfinger, Abela,
& Yao (2009)
406 .30 .34 AI-ext RBQ-A Journal article China 50 16.2 School Average household
income $3.1k
Auerbach et al. (2011)
Canada 255 .04 .04 AI CES-D Journal article Canada 57 14.48 School 79.5
China 405 .15 .16 AI CES-D Journal article China 50 16.18 School
Baller (2011) 487 .22 .28 AI LS Thesis U.S.A. 74 Over 18 Student 82.3
Belk (1984) 338 .18 .31 BMS LS Journal article U.S.A. 33 Over 18 General
.23 .39 BMS Happy
Bertran, Casas &
Gonzalez (2009) 5,140 .04 .06 Casas PWB Conference
paper Spain 50 Under 12 School
Bottomley, Nairn,
Kasser, Ferguson,
& Ormrod (2010) 142 .08 .10 CO RSE Journal article U.S.A. 100 Under 12 School 90
Brdar (2006) 439 .04 .05 AI-FS BPNS–
competence Journal article Hungary 55 19.0 Student
.08 .10 AI-FS BPNS–
autonomy
Brown & Kasser (2005)
Study 1 206 .22 .35 Mat Happy Journal article U.S.A. 44 14.2 School 96
Study 2 400 .31 .41 AI Affect Balance Journal article U.S.A. 66 43.7 General Average individual
income
$33.9k; 77%
attended higher
education; all
completed high
school or
equivalent
91
Buijzen & Valkenburg
(2003) 360 .03 .04 CM LSC Journal article Netherlands 51 10.0 School 63% attended
higher
education; 12%
did not complete
high school or
equivalent
Burroughs &
Rindfleisch (2002) 373 .18 .20 MVS–18 DASS Journal article U.S.A. 52 47.0 General Average household
income $52k;
48% attended
higher education
85
Carver & Baird (1998) 246 .31 .45 AI-reg ISA Journal article U.S.A. Over 18 Student
Casas, Figuer, Gonzalez,
& Malo (2007)
Child sample 1,618 .08 .11 Casas PWB Journal article Spain 53 14.0 School
Parent sample 723 .05 .08 Casas parent PWB Journal article Spain Over 18 School
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890 DITTMAR, BOND, HURST, AND KASSER
Table 4 (continued)
Study N
a
r
b
Materialism
measure Outcome
measure Type of
publication Country %
female Average age/age
group (years) Population
Average income/
educational
background % White
Casas, Gonzalez, Figuer,
& Coenders (2004) 968 .01 .02 Casas LS Journal article Spain 51 14.0 School
Chan & Joseph (2000) 107 .21 .31 AI-FS ISA Journal article U.K. 1 26.5 Student
.16 .20 AI-FS RSE
Chang & Arkin (2002) 416 .19 .24 MVS–18 SD Journal article U.S.A. Over 18 Student
Christopher, Drummond,
Jones, Marek, &
Therriault (2006) 204 .28 .33 MVS–18 SD Journal article U.S.A. 69 24.9 General
Christopher, Kuo,
Abraham, Noel, &
Linz (2004)
159 .22 .28 MVS–18 PANAS–
Negative
Affect
Journal article U.S.A. 53 Over 18 Student
Christopher, Lasane,
Troisi, & Park
(2007) 277 .20 .24 MVS–18 SWLS Journal article U.S.A. 64 18.8 Student
Christopher, Saliba, &
Deadmarsh (2009) 440 .35 .42 MVS–18 PANAS–
Negative
Affect
Journal article U.S.A. 52 39.0 General
Christopher & Schlenker
(2004) 297 .15 .18 MVS–18 PANAS–
Negative
Affect
Journal article U.S.A. 56 Over 18 Student
Coenders, Casas, Figuer,
& González (2005)
Brazilian sample 765 .04 .06 Money LS Journal article Brazil 49 13.9 School
Indian sample 1,066 .02 .04 Money LS Journal article India 49 13.9 School
Norwegian sample 823 .01 .01 Money LS Journal article Norway 49 13.9 School
South African sample 781 .03 .05 Money LS Journal article South Africa 49 13.9 School
Spanish sample 3,050 .01 .01 Money LS Journal article Spain 49 13.9 School
Dik, Sargent, & Steger
(2008) 225 .06 .07 MCS MLQ Journal article U.S.A. 81 19.5 Student 86
Dittmar (2005a)
Study 1 330 .42 .48 MVS–18 CBS Journal article U.K. 73 39.5 General Average individual
income
$28.8k
Study 2 250 .49 .59 MVS–18 CBS Journal article U.K. 53 34.2 General Average individual
income
$14.4k
95
Study 3 195 .31 .38 MVS–18 CBS Journal article U.K. 52 Under 12 School
Dittmar (2005b)
Study 2 239 .39 .45 MVS–18 SDI Journal article U.K. 100 39.2 General
Study 3 females 58 .28 .32 MVS–18 SDI Journal article U.K. 100 22.2 Student
Study 3 males 68 .09 .10 MVS–18 SDI Journal article U.K. 0 21.8 Student (table continues)
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891
MATERIALISM AND WELL-BEING
Table 4 (continued)
Study N
a
r
b
Materialism
measure Outcome
measure Type of
publication Country %
female Average age/age
group (years) Population
Average income/
educational
background % White
Dittmar & Kapur (2010)
Older Indian sample 109 .61 .71 MVS–15 CBS 4
items Unpublished MS India 53 33.9 General Average individual
income $3.4k
Older U.K. sample 127 .34 .41 MVS–15 CBS 4
items Unpublished MS U.K. 50 31.1 General Average individual
income
$25.1k
Younger Indian
sample 109 .67 .78 MVS–15 CBS 4
items Unpublished MS India 53 33.9 General Average individual
income
$30.4k
Younger U.K. sample 127 .47 .57 MVS–15 CBS 4
items Unpublished MS U.K. 50 31.1 General Average individual
income
$25.1k
Dittmar, Long, & Bond
(2007) 126 .43 .47 MVS–15 CBS Journal article U.K. 46 21.9 Student 99
Donelly, Iyer, & Howell
(2012) 201 .33 .41 MVS–15 CB Journal article U.S.A. 66 34.93 General 71.8
Felix & Garza (2012) 339 .22 .26 MVS–9 SWLS Journal article Mexico 100 18.7 Student
Flouri (2004) 2,218 .22 .29 Mat Value SDQ Journal article U.K. 45 Under 12 School 62
Froh, Emmons, Card,
Bono, & Wilson 1,035 .06 .07 MVS–15 CES-D Journal article U.S.A. 49 15.67 School 64.7
K. M. Frost & Frost
(2000)
Romanian sample 217 .12 .17 AI-FS SWLS Journal article Romania 56 21.5 Student
U.S. sample 201 .17 .21 AI-FS SWLS Journal article U.S.A. 43 Over 18 Student
R. O. Frost, Kyrios,
McCarthy, &
Matthews (2007) 127 .40 .48 MVS–18 SAM Journal article U.S.A. 1 Over 18 Student
Furnham & Okamura
(1999) 277 .08 .13 Tycoon Rubinstein Journal article U.K. 51 35.8 General Average individual
income
$12.3k; 9.4%
attended higher
education; 10%
did not complete
high school or
equivalent
Galand, Boudrenghien,
& Rose (2012) 333 .20 .24 AI-intabs LS–15 Journal article Belgium 58 41 General
Garðarsdóttir (2006)
Study 1 Icelandic
sample 146 .28 .34 MVS–18 SWLS 2
affect items Thesis Iceland 71 24.7 Student
Study 1 U.K. sample 145 .16 .19 MVS–18 SWLS 2
affect items Thesis U.K. 64 24.2 Student
Study 2 Icelandic
sample 968 .01 .01 AI LS Thesis Iceland 50 44.1 General
Study 2 U.K. sample 1,000 .02 .03 AI LS Thesis U.K. 56 42.1 General
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892 DITTMAR, BOND, HURST, AND KASSER
Table 4 (continued)
Study N
a
r
b
Materialism
measure Outcome
measure Type of
publication Country %
female Average age/age
group (years) Population
Average income/
educational
background % White
Study 3 Icelandic
sample 476 .26 .30 MVS–18 SWLS
PANAS Thesis Iceland 75 38.0 General Average individual
income
$52.0k
Study 3 U.K. sample 223 .16 .18 MVS–18 SWLS
PANAS Thesis U.K. 62 33.7 General Average individual
income
$43.1k
Garðarsdóttir, Dittmar,
& Aspinall (2009)
Study 1 Iceland
sample 139 .24 .28 AI-FS SWLS 2
affect items Journal article Iceland 73 24.8 Student
Study 1 U.K. sample 145 .11 .13 AI-FS SWLS 2
affect items Journal article U.K. 64 24.2 Student
Study 2 261 .16 .19 AI-FS SWLS 2
affect items Journal article U.K. 57 38.9 General Average individual
income
$55.5k
Georgellis, Tsitsianis, &
Yin (2009)
Scandinavian sample
2002 6,834 .14 .24 ESS LS Journal article Scandinavia Over 18 General
Scandinavian sample
2004 6,835 .13 .22 ESS LS Journal article Scandinavia Over 18 General
Southern European
sample 2002 3,804 .24 .42 ESS LS Journal article Southern
Europe Over 18 General
Southern European
sample 2004 3,804 .17 .30 ESS LS Journal article Southern
Europe Over 18 General
Western European
sample 2002 10,907 .14 .25 ESS LS Journal article Western
Europe Over 18 General
Southern European
sample 2002 10,907 .14 .25 ESS LS Journal article Western
Europe Over 18 General
Giacalone & Jurkiewicz
(2004) 111 .10 .12 R-MPMI PILT Journal article U.S.A. 56 Over 18 Student
Giacomantonio,
Mannetti, & Pierro
(2013)
370 .27 .36 MVS–18 PANAS–
Negative
Affect
Journal article Italy 57 Over 18 General 31.9
M. E. Goldberg, Gorn,
Peracchio, &
Bamossy (2003) 547 .03 .05 YMS PHappy Journal article U.S.A. 52 11.5 School
Gomez, Alleman, &
Grob (2012)
Young adults 251 .49 .58 GI-I SWB Journal article Germany 42 19.2 Student
Middle-age adults 242 .20 .24 GI-I SWB Journal article Germany 67 47.49 General
Older adults 225 .38 .45 GI-I SWB Journal article Germany 74 75.05 General
Gornik-Durose & Janiec
(2010) 247 .16 .18 MVS–18 SWLS Unpublished MS Poland 73 23.3 Student
Howell (2010) 2,884 .34 .39 MVS–18 IBTS–
cognitive Unpublished MS U.S.A. 74 Over 18 General 54
.51 .60 MVS–18 IBTS–affective (table continues)
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893
MATERIALISM AND WELL-BEING
Table 4 (continued)
Study N
a
r
b
Materialism
measure Outcome
measure Type of
publication Country %
female Average age/age
group (years) Population
Average income/
educational
background % White
Hudders & Pandelaere
(2012) 2,206 .02 .03 MVS–15 PANAS–
Positive
Affect
Journal article U.S.A. 50 40.02 General
Izdenczyová (2009) 234 .32 .40 PVQ40 SEHP Journal article Czech Republic 90 21.1 Student
Jankovic (2006)
Croatian economics
students 143 .30 .37 MVS–18 SWLS 2
affect items Thesis Croatia 84 20.8 Student
Croatian psychology
students 36 .35 .43 MVS–18 SWLS 2
affect items Thesis Croatia 84 20.8 Student
German economics
students 44 .40 .48 MVS–18 SWLS 2
affect items Thesis Germany 75 21.8 Student
German psychology
students 75 .23 .28 MVS–18 SWLS 2
affect items Thesis Germany 75 21.8 Student
Study 2 Croatian
sample 100 .27 .31 MVS–18 SWLS ABS Thesis Croatia 77 23.9 Student 99
Study 2 New Zealand
sample 72 .25 .30 AI-reg SWLS ABS Thesis New Zealand 67 21.3 Student
Study 2 U.K. sample 100 .42 .48 AI-reg SWLS ABS Thesis U.K. 72 20.0 Student 92
Study 4 Croatian
sample 169 .27 .33 MVS–9 SWLS 2
affect items Thesis Croatia 72 33.3 General Average individual
income
$11.1k
Study 4 U.K. sample 158 .12 .14 MVS–9 SWLS 2
affect items Thesis U.K. 59 30.6 General Average individual
income
$34.5k
U.K. economics
students 59 .07 .09 MVS–18 SWLS 2
affect items Thesis U.K. 60 21.5 Student
U.K. psychology
students 157 .22 .29 MVS–18 SWLS 2
affect items Thesis U.K. 60 21.5 Student
Kashdan & Breen
(2007) 144 .28 .31 MVS–15 SIAS Journal article U.S.A. 79 23.8 Student 54
Kasser (2005) 206 .11 .18 MVS–8 Cigarette use Journal article U.S.A. 44 14.2 School 96
.15 .24 MVS–8 Alcohol use
Kasser & Ahuvia (2002) 92 .20 .25 MVS–18 Physical health Journal article Singapore 72 21.1 Student
Kasser et al. (2014)
Study 4 adults 92 .11 .13 AI-ext PANAS–
Negative
affect
Journal article U.S.A. 83 45.6 General 51% family
income
$100,000
96
Study 4 adolescents 92 .15 .17 AI-ext HSC–anxiety Journal article U.S.A. 50 12.4 Under 18 51% family
income
$100,000
96
Kasser & Ryan (1993)
Study 1 118 .47 .67 AI-reg ISA Journal article U.S.A. 64 Over 18 Student 71
Study 2 117 .24 .29 AI-reg CES-D Journal article U.S.A. 67 Over 18 Student 72
Study 3 140 .49 .59 AI-reg CGAS Journal article U.S.A. 47 18.0 General 21% did not
complete high
school or
equivalent
67
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894 DITTMAR, BOND, HURST, AND KASSER
Table 4 (continued)
Study N
a
r
b
Materialism
measure Outcome
measure Type of
publication Country %
female Average age/age
group (years) Population
Average income/
educational
background % White
.31 .40 AI-reg CMHI–social
productivity
.47 .60 AI-reg DICA
Kasser & Ryan (1996)
Study 1 100 .29 .35 AI-reg CES-D Journal article U.S.A. 76 38.0 General Average household
income $35k 93
Study 2 177 .30 .35 AI-reg CES-D Journal article U.S.A. 56 Over 18 Student 67
Kasser & Ryan (2001)
Student Sample A 120 .36 .51 AI Well-being Book chapter U.S.A. 49 Over 18 Student 77
Student Sample B 261 .36 .51 AI Drug use Book chapter U.S.A. 59 Over 18 Student 89
Khanna & Kasser
(2010)
Danish sample 48 .18 .21 AI-ext HSC–anxiety Unpublished MS Denmark 65 24.4 Student
Indian sample 50 .20 .23 AI-ext HSC–anxiety Unpublished MS India 58 19.1 Student
U.S. sample 46 .17 .20 AI-ext HSC–anxiety Unpublished MS U.S.A. 67 19.9 Student
Kim, Kasser, & Lee
(2003)
South Korean sample 328 .11 .14 AI HSC–anxiety Journal article South Korea 53 Over 18 Student
U.S. sample 215 .12 .15 AI HSC–anxiety Journal article U.S.A. 57 Over 18 Student
Klonowicz, Cieslak, &
Eliasz (2004) 1,221 .12 .16 Extrinsic SSC Journal article Poland 58 47.9 General
Komlósi, Sándor, Márk,
Éva, & Dóra (2006) 537 .14 .16 AI-ext BDI Journal article Hungary 68 Over 16 General
Ku (2009)
Middle-age group 102 .68 .87 YMS CBS Thesis Hong Kong 43 14.2 School
Oldest age group 97 .70 .84 YMS CBS Thesis Hong Kong 58 17.7 School
Youngest age group 98 .02 .03 YMS SLSS 2
affect scores Thesis Hong Kong 51 9.6 School
Kwak, Zinkhan, &
French (2001) 76 .26 .29 MVS–18 PII–alcohol Journal article U.S.A. 53 Over 18 Student
.11 .12 MVS–18 PII–tobacco
.00 .00 MVS–18 PII–drug
.10 .15 MVS–18 Alcohol use
.07 .10 MVS–18 Tobacco use
.04 .06 MVS–18 Drug Use
Index
La Barbera & Gurhan
(1997) 241 .06 .11 WW CSWB Journal article U.S.A. 54 36.9 General Average household
income $40k;
27% attended
higher education
Lekes, Gingras,
Philippe, Koestner,
& Fang (2010)
Chinese sample 515 .13 .16 AI-ext PANAS
SCS Journal article China 56 15.2 School
U.S. sample 567 .05 .06 AI-ext PANAS
SCS Journal article U.S.A. 48 14.2 School
(table continues)
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895
MATERIALISM AND WELL-BEING
Table 4 (continued)
Study N
a
r
b
Materialism
measure Outcome
measure Type of
publication Country %
female Average age/age
group (years) Population
Average income/
educational
background % White
Luna-Arocas & Tang
(2004) 311 .09 .11 MES–Success LS-2 Journal article U.S.A. &
Spain 46 42.7 General Average individual
income
$40.3k
Malka & Chatman
(2003) 124 .00 .00 ExtWork SWLS
PANAS Journal article U.S.A. 47 28.0 Student Average individual
income
$80.0k
Manolis & Roberts
(2012) 1,329 .06 .08 YMS CB CBS Journal article U.S.A. 42 14.7 School 51
Manriquez (2010)
Chilean sample 259 .17 .18 AI-ext CES-D Thesis Chile 53 34.7 General 100% attended
higher education
U.K. sample 949 .06 .07 AI-ext CES-D Thesis U.K. 59 44.6 General Average individual
income
$40.3k; 100%
attended higher
education
Martos & Kopp (2012) 4,841 .34 .40 AI-14-I WHO-5 Journal article Hungary 58.8 48.3 General
Miller (2009)
Study 1 839 .18 .27 MVS/IPIP INE Thesis U.S.A. 63 19.8 Student
Study 3 603 .17 .26 MVS/IPIP INE Thesis U.S.A. 57 64.6 General
Mueller, Claes, et al.
(2011)
Male 124 .46 .59 MVS–11 CB Journal article Germany &
Belgium 0 22.9 Student
Female 286 .35 .45 MVS–11 CB Journal article Germany &
Belgium 100 22.9 Student
Mueller, Mitchell, et al.
(2011) 387 .38 .42 MVS–11 Internet use Journal article U.S.A. 38.8 Student
.45 .51 MVS–11 CB
Nickerson, Schwartz,
Diener, &
Kahneman (2003)
$0.5k average
household income 25 .28 .49 Money Health Journal article U.S.A. 56 18.0 Student Average household
income $0.5k
$5.5k average
household income 53 .10 .18 Money Health Journal article U.S.A. 51 18.0 Student Average household
income $5.5k 87
$15k average
household income 184 .14 .25 Money Health Journal article U.S.A. 56 18.2 Student Average household
income $15k
$25k average
household income 366 .09 .16 Money Health Journal article U.S.A. 60 18.1 Student Average household
income $25k
$40k average
household income 1,353 .00 .00 Money Health Journal article U.S.A. 59 18.1 Student Average household
income $40k
$62.5k average
household income 2,309 .04 .07 Money Health Journal article U.S.A. 54 18.1 Student Average household
income
$62.5k
$87.5k average
household income 1,951 .02 .04 Money Health Journal article U.S.A. 52 18.1 Student Average household
income
$87.5k
90
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896 DITTMAR, BOND, HURST, AND KASSER
Table 4 (continued)
Study N
a
r
b
Materialism
measure Outcome
measure Type of
publication Country %
female Average age/age
group (years) Population
Average income/
educational
background % White
$125k average
household income 2,057 .04 .07 Money Health Journal article U.S.A. 50 18.1 Student Average household
income
$125k
92
$175k average
household income 937 .03 .05 Money Health Journal article U.S.A. 52 18.0 Student Average household
income
$175k
93
$290k average
household income 1,430 .08 .14 Money Health Journal article U.S.A. 50 18.0 Student Average household
income
$290k
92
Niemiec, Ryan, & Deci
(2009) 147 .11 .13 AI-FS STAI-6 Journal article U.S.A. 70 Over 18 Student 80
Norris, Lambert,
DeWall, &
Fincham (2012) 61 .22 .23 MVS–18 AA Journal article U.S.A. 82 Over 18 Student
Norris & Larsen (2011) 101 .28 .33 MVS–18 SWLS Journal article U.S.A. 64 20.6 Student 87
Opree, Buijzen, van
Reijmersdal, &
Valkenburg (2011) 965 .28 .33 MSC–18 LD Journal article Netherlands 50 8–11 School
Otero-López, &
Villardefrancos
(2013) 667 .51 .57 MSC–18 GABS Journal article Spain 100 38.4 General
Otero-López,
Villardefrancos,
Castro, & Santiago
(2011) 469 .58 .64 MSC–18 GABS Journal article Spain 100 37.3 General
Pepper, Jackson, &
Uzzell (2009) 260 .37 .46 MVS–15 Frugal Journal article U.K. 65 50.0 General Average individual
income
$50.8k; 59%
attended higher
education
Pham, Yap, & Dowling
(2012) 118 .44 .54 MSC–18 CB Journal article Australia 62 27.2 General
Piko & Keresztes (2006) 1,109 .24 .32 AI-ext Physical
activity Journal article Hungary 60 16.5 School
Pinquart, Silbereisen, &
Frohlich (2009) 334 .08 .12 TP PILT Journal article Germany 42 54.4 General
Reeves, Baker, &
Truluck (2012)
Male 63 .29 .34 MVS–18 SCC Journal article U.S.A. 0 General
.07 .08 MVS–18 RSE
Female 106 .24 .28 MVS–18 SCC Journal article U.S.A. 100 General
.19 .22 MVS–18 RSE
Richins (2010) 295 .20 .29 MVS–9 Happy Unpublished MS U.S.A. 53 Over 18 General 53% not
completed high
school or
equivalent (table continues)
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897
MATERIALISM AND WELL-BEING
Table 4 (continued)
Study N
a
r
b
Materialism
measure Outcome
measure Type of
publication Country %
female Average age/age
group (years) Population
Average income/
educational
background % White
Richins & Dawson
(1992)
Study 3 235 .12 .15 MVS–18 RSE Journal article U.S.A. Over 18 General
Study 4 205 .34 .49 MVS–18 LS–fun Journal article U.S.A. Over 18 General
Rindsfleisch, Burroughs,
& Wong (2009) 314 .37 .41 MVS–9 SD Journal article U.S.A. 49 49.0 General Average household
income
$59.6k; 41%
attended higher
education
Robak, Chiffriller, &
Zappone (2007) 157 .15 .21 Money PANAS–
Negative
Affect
Journal article U.S.A. 64 21.4 Student 73
Roberts, Manolis, &
Tanner (2003)
Divorced sample 174 .40 .50 MVS–11 CBS Journal article U.S.A. 49 13.7 School 81
Nondivorced sample 494 .53 .67 MVS–11 CBS Journal article U.S.A. 49 13.7 School 81
Romero, Gomez-
Fraguela, & Villar
(2012)
583 .30 .36 AI-int PANAS–
Positive
Affect
Journal article Spain 71 34.65 General
Rose (2007) 238 .34 .42 MVS–15 CB Journal article U.S.A. 62 20.0 Student 77
Ryan et al. (1999)
Female Russian
sample 103 .03 .03 AI CES-D Journal article Russia 100 Over 18 Student
Female U.S. sample 69 .16 .18 AI CES-D Journal article U.S.A. 100 Over 18 Student
Male Russian sample 80 .16 .18 AI CES-D Journal article Russia 0 Over 18 Student
Male U.S. sample 47 .34 .37 AI CES-D Journal article U.S.A. 0 Over 18 Student
Sardžoska & Tang
(2009)
Sample from private
organizations 208 .05 .06 LOM GSS-LS Journal article Macedonia 54 34.9 General Average individual
income $4.7k
Sample from public
organizations 307 .03 .04 LOM GSS-LS Journal article Macedonia 57 41.5 General Average individual
income $3.4k
Saunders & Munro
(2000)
Study 1 302 .19 .22 MVS–18 BAI Journal article Australia 75 23.0 Student
Study 2 87 .22 .25 MVS–18 BDI Journal article Australia 62 27.7 Student
Study 3 80 .17 .20 MVS–18 Comrey Journal article Australia 65 26.8 Student
Schmuck (2001)
Sample C 76 .06 .07 AI HSC–anxiety Book chapter Germany 71 18.3
General population
sample 61 .19 .22 AI HSC–anxiety Book chapter Germany 61 47.4 General
Student Sample A 40 .32 .37 AI CES-D Book chapter Germany 75 23.3 Student
Student Sample B 150 .00 .00 AI HSC–anxiety Book chapter Germany 60 21.7 Student
Schmuck, Kasser, &
Ryan (2000) 83 .11 .13 AI CES-D Journal article Germany 61 Over 18 Student
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898 DITTMAR, BOND, HURST, AND KASSER
Table 4 (continued)
Study N
a
r
b
Materialism
measure Outcome
measure Type of
publication Country %
female Average age/age
group (years) Population
Average income/
educational
background % White
Sheldon (1998) 221 .19 .24 AI PANAS–
Negative
Affect
Unpublished raw
data U.S.A. 67 Over 18 Student
Sheldon (2000a)
Fall: nursing students 38 .03 .04 AI ISA Unpublished raw
data U.S.A. Over 18 Student
Fall: law students 236 .07 .09 AI BDI Unpublished raw
data U.S.A. 45 Over 18 Student
Sheldon (2000b) 175 .20 .25 AI PANAS–
Negative
Affect
Unpublished raw
data U.S.A. 61 20.1 Student
Sheldon (2000c) 279 .15 .19 AI SWLS
PANAS Unpublished raw
data U.S.A. 62 20.8 Student 88
Sheldon (2001a)
Arkansas law students 133 .21 .32 AI ISA Unpublished raw
data U.S.A. Over 18 Student
Florida law students 162 .10 .16 AI ISA Unpublished raw
data U.S.A. Over 18 Student
Nursing students 66 .03 .04 AI ISA Unpublished raw
data U.S.A. Over 18 Student
Sheldon (2001b) 127 .14 .18 AI PANAS–
Positive
Affect
Unpublished raw
data U.S.A. 56 Over 18 Student
Sheldon (2001c) 234 .03 .04 AI PANAS–
Negative
Affect
Unpublished raw
data U.S.A. 51 Over 18 Student
Sheldon (2001d) 198 .06 .08 AI PANAS–
Negative
Affect
Unpublished raw
data U.S.A. 61 Over 18 Student 83
Sheldon (2001e) 99 .03 .04 AI PANAS–
Negative
Affect
Unpublished raw
data U.S.A. Over 18 Student
Sheldon (2002a) 334 .20 .26 AI PANAS–
Negative
Affect
Unpublished raw
data U.S.A. 62 Over 18 Student 85
Sheldon (2002b) 447 .21 .27 AI PANAS–
Negative
Affect
Unpublished raw
data U.S.A. 57 Over 18 Student 84
Sheldon (2002c) 255 .10 .13 AI PANAS–
Negative
Affect
Unpublished raw
data U.S.A. 49 Over 18 Student
Sheldon (2002d) 64 .16 .21 AI PANAS–
Negative
Affect
Unpublished raw
data U.S.A. Over 18 Student
Sheldon (2002e) 173 .09 .11 AI PANAS–
Negative
Affect
Unpublished raw
data U.S.A. 61 Over 18 Student
(table continues)
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899
MATERIALISM AND WELL-BEING
Table 4 (continued)
Study N
a
r
b
Materialism
measure Outcome